mlpack benchmarks

This page contains benchmarks for the various algorithms implemented
in mlpack 1.0.10. When applicable, timing results
are also given for other libraries. Currently, benchmarks are provided for scikit-learn, the SHOGUN machine learning toolbox, Weka 3, mlpy, and standard MATLAB
implementations. If you don't see benchmarks for your favorite library or
algorithm, feel free to file a bug
report or consult the documentation for
the automatic benchmarking system and write a script.

The automatic benchmarking system was developed as a Google Summer
of Code 2013
project by Marcus Edel and
improved by Anand Soni during GSoC 2014, and is maintained separately on Github.

Below, you may select one of many interactive JavaScript visualizations for
inspecting the benchmarking results. At this time, we are still adding results
(especially historical results). If you are interested in the previous
non-interactive visualizations, which included memory usage graphs for
mlpack methods, click here.